Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study.

Raghuram, Kamini; Orlandi, Silvia; Church, Paige; Luther, Maureen; Kiss, Alex; Shah, Vibhuti

Raghuram, Kamini; Orlandi, Silvia; Church, Paige; Luther, Maureen; Kiss, Alex; Shah, Vibhuti.

Afiliación

Raghuram K; Division of Neonatology, Department of Paediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada.
Orlandi S; Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON M4G 1R8, Canada.
Church P; Department of Electrical, Electronic, and Information Engineering, Guglielmo Marconi (DEI), University of Bologna, 40136 Bologna, Italy.
Luther M; Division of Neonatology, Department of Paediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada.
Kiss A; Neonatology and Neonatal Follow-Up, Women and Babies Program, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada.
Shah V; Neonatology and Neonatal Follow-Up, Women and Babies Program, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada.

Children (Basel) ; 9(6)2022 Jun 07.

Article en En | MEDLINE | ID: mdl-35740780

Palabras clave

cerebral palsy; computer vision; early detection; early intervention; general movements assessment; machine learning; neonatal follow-up; preterm infant

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Idioma: En Revista: Children (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Suiza

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